Ruby Video
Garbage Collection

Faster Apps, No Memory Thrash: Get Your Memory Config Right

#cruby
#developer-tools
#performance
#ruby
#garbage-collection
#optimization
#memory-management

Faster Apps, No Memory Thrash: Get Your Memory Config Right

by Noah Gibbs

In this presentation at RubyKaigi 2018, Noah Gibbs discusses optimizing memory configurations for Ruby applications to enhance performance and prevent memory-related issues. The talk addresses the complexities of Ruby's memory system and introduces practical strategies for efficient memory management.

Key Points:

  • Understanding Ruby's Memory System:

    • Ruby differentiates between tiny, small, and big objects based on size and memory allocation.
    • Tiny objects fit within their references and are efficient, whereas small and big objects impact performance due to costly memory allocation.

  • Garbage Collection:

    • Ruby uses a generational mark-sweep garbage collector that optimizes how and when memory is reclaimed based on object age.
    • Garbage collection consists of major and minor collections, with the former checking all objects and the latter focusing on newer objects.
    • Manual triggering of garbage collection can be done using GC.start.

  • Improving Garbage Collection Performance:

    • Reducing object creation leads to less garbage, making garbage collection faster.
    • Efficient algorithms, caching, and pre-calculation can minimize garbage generation.
    • Using destructive operations can help reuse data efficiently, particularly for strings and arrays.

  • Tools and Configuration:

    • Introducing the mmm tool, which simplifies memory optimization by setting environment variables for better allocation.
    • Insights into the internal memory status are obtainable through GC.stat, allowing users to adjust their Ruby environment for optimal performance.

  • Alternative Memory Allocators:

    • Exploring memory allocators like jemalloc and tcmalloc can improve speed and efficiency by enhancing memory allocation processes.
    • Leveraging the benefits of these allocators can yield performance boosts of 10-12%.

  • Continuous Improvement:

    • Regular profiling with tools like GC::Profiler is essential to identify garbage collection duration and its impact on application responsiveness.
    • It's important to keep Ruby updated to leverage enhancements in memory management features.

Conclusions:

  • Effective memory management is critical for optimizing the performance of Ruby applications.
  • Users should regularly assess their applications for memory issues and consider using helpful tools and configurations to minimize memory thrash and improve response times.
  • Questions and further discussions were encouraged at the end of the presentation, emphasizing an open approach to solving memory-related challenges in Ruby applications.
00:00:01.399 Hello everyone! It's great to see you all here.
00:00:07.319 I'm Noah Gibbs, and today we're going to talk about improving memory configurations for Ruby applications.
00:00:14.250 Specifically, we'll focus on how to optimize Ruby's memory usage to prevent performance issues.
00:00:20.820 I also want to take a moment to express my gratitude to AppFolio, where I'm a Ruby fellow.
00:00:30.430 They support my efforts in writing blog posts and running extensive benchmarks.
00:00:36.540 Now, let's dive into the topic at hand.
00:00:42.690 You're all here to learn how to improve the performance of Ruby applications facing memory problems.
00:00:49.559 Before we start, let me share a bit about my life.
00:00:54.840 I recently welcomed a three-month-old baby who is incredibly cute, which explains why I may look a bit tired.
00:01:07.400 Life is busy with two other kids and activities like visiting the City Museum.
00:01:14.520 If you're not familiar with it, I highly recommend checking out the beautiful hand-painted maps.
00:01:21.299 Now, let's focus on Ruby and its memory system.
00:01:26.640 To understand how to improve Ruby's performance, it's important to comprehend how its memory system functions.
00:01:33.450 We will explore the concepts of tiny, small, and big objects in Ruby.
00:01:39.180 Tiny objects are the smallest in Ruby and fit entirely inside their references.
00:01:44.790 Ruby maintains 64-bit references, generally pointing to something, but tiny objects fit in that reference.
00:01:52.070 These objects can include integers from about negative and positive one billion, symbols, floating-point numbers, and special values.
00:01:57.450 The significance of this is that tiny objects are efficient and fast.
00:02:02.909 When we discuss symbols being faster than strings, it refers to how symbols fit within the reference itself.
00:02:09.149 Conversely, let's now examine small objects.
00:02:15.990 Small objects occupy 40-byte slots, allowing for short strings and arrays, as well as small big decimal numbers.
00:02:23.730 Class instances with only a few instance variables also fit into these slots.
00:02:28.770 Allocating memory slots for small objects is economical since the memory allocator is called incrementally.
00:02:35.250 If small objects exceed their size limitations, they become big objects.
00:02:41.100 Big objects have more expensive allocation calls whenever they are created or resized.
00:02:49.380 Consequently, they are crucial to track down when diagnosing memory issues in your Ruby applications.
00:02:55.500 Now let's discuss garbage collection.
00:03:01.560 Garbage collection is the main aspect to address when dealing with memory in Ruby.
00:03:06.960 Ruby utilizes a generational mark-sweep garbage collector.
00:03:12.000 While it may not be the top garbage collector, it works well.
00:03:17.250 Generational garbage collection checks newer objects more frequently than older ones.
00:03:22.560 Objects that remain for a longer time are less frequently marked for collection since older objects might still be in use.
00:03:30.510 The mark phase examines all available objects to identify those no longer in use.
00:03:36.860 Once identified, the sweep phase collects and clears memory from those marked objects.
00:03:45.130 While Ruby's garbage collector is efficient, alternatives like those in the JVM are even superior.
00:03:50.480 Generational garbage collection works through two main types: major and minor.
00:03:58.190 The major garbage collection evaluates all objects, while minor garbage collection focuses specifically on newer ones.
00:04:04.640 Major collections occur when certain thresholds are crossed, prompting a complete check.
00:04:10.160 You can also manually trigger major garbage collection by calling `GC.start`, which initiates a thorough sweep.
00:04:17.670 During an application's startup phase, Ruby starts with a modest memory allocation.
00:04:24.750 As applications run, they accumulate more memory through a cycle of growth and garbage collection.
00:04:30.340 This cycle involves growing memory usage, performing garbage collection, and expanding available slots as needed.
00:04:36.860 The expansion phase results from running out of allocated memory slots.
00:04:41.680 Although most applications eventually stabilize to a certain size, monitoring growth patterns is important.
00:04:47.410 The overall goal is to recognize how your application behaves during its lifecycle and identify possible areas for optimization.
00:04:58.260 Now, let's discuss how to tackle and resolve memory issues.
00:05:06.640 The most effective way to improve garbage collection performance is to reduce object creation.
00:05:14.240 Less garbage generated leads to more efficient and faster garbage collection.
00:05:21.100 Utilizing more efficient algorithms, caching, or pre-calculating values can help minimize garbage.
00:05:27.460 Additionally, when dealing with large objects, consider combining multiple smaller objects into a single entity.
00:05:36.090 You can also take advantage of destructive operations to reuse data efficiently.
00:05:41.840 For instance, methods that modify strings and arrays in place reduce the creation of new objects.
00:05:46.080 This is critical for situations where low memory usage is imperative.
00:05:51.010 Further, using tools like `GC.stat` will provide insights into your memory configuration.
00:05:57.450 This tool can help identify available slots and how often garbage collections occur.
00:06:04.030 After gathering this information, adjusting environment variables can lead to improvements.
00:06:10.090 You can utilize options like `RUBY_GC_HEAP_FREE_SLOTS` to manage memory allocation effectively.
00:06:20.000 Proper allocation means starting your application with an optimal number of slots.
00:06:26.810 Maintaining a healthy ratio of free slots will also keep performance steady.
00:06:32.780 For instance, the `RUBY_GC_HEAP_GROWTH_MAX_SLOTS` variable can help expand available memory limits.
00:06:39.950 Considering all these aspects contributes greatly to effective memory management in Ruby.
00:06:46.540 Now, I want to introduce a tool I've been developing called `mmm`.
00:06:52.290 This tool aims to simplify the process of tuning memory configurations for Ruby applications.
00:06:59.980 By setting appropriate environment variables, it allows for optimal allocation from the start.
00:07:05.890 After running your application, you can use `mmm` to determine the suitable allocation sizes.
00:07:10.640 This can significantly improve startup times for large applications.
00:07:16.680 It's important to consider the impact of memory management on your application's performance.
00:07:22.930 Examples of real-world applications effectively using this concept showcase decreased warm-up times.
00:07:30.110 Therefore, if you're encountering performance hiccups during startup, this tool could be beneficial.
00:07:37.360 Next, I'd like to touch on memory allocators and their importance.
00:07:44.300 Most operating systems come with a memory allocator by default, like `malloc`.
00:07:52.600 However, there are alternative implementations, such as `jemalloc`, that offer significant advantages.
00:07:58.750 Increased efficiency in allocating memory leads to faster application performance.
00:08:05.010 For Ruby, integrating with `jemalloc` has been a game changer for several applications.
00:08:11.560 Testing has shown marked improvements, especially when running under load.
00:08:17.780 Implementing these optimizations could yield a 10-12% increase in overall speed.
00:08:23.920 Another allocator, `tcmalloc`, may also provide slight performance boosts.
00:08:30.570 It's crucial to evaluate the performance implications of your application and the allocator you choose.
00:08:37.200 To round out this discussion, always prioritize being on the latest version of Ruby.
00:08:43.700 This optimizes garbage collection and can lead to performance improvements.
00:08:51.100 As Ruby evolves, it brings enhanced features to memory management.
00:08:57.800 Lastly, addressing potential fragmentation issues and common pitfalls can yield better performance.
00:09:05.900 Make sure to regularly profile your application to identify areas needing improvement.
00:09:12.040 Utilizing tools like `GC::Profiler` can provide valuable insights.
00:09:19.450 Monitor garbage collection statistics for duration and frequency of pauses.
00:09:26.040 This will help determine if memory management is causing noticeable slowdowns.
00:09:35.310 As a practical exercise, compile Ruby with additional options to enhance profiling.
00:09:41.200 After extracting data, analyze it for any abnormalities.
00:09:48.150 Keep experimenting with different configurations to find an optimal setup.
00:09:54.070 The understanding of memory management will make a significant difference in Ruby applications.
00:10:00.350 As we conclude, feel free to ask any questions regarding memory, garbage collection, or anything we've discussed.
00:10:09.910 I'm here to assist and clarify anything that may be unclear.
00:10:16.790 Understanding and managing memory effectively can greatly improve performance.
00:10:21.269 Thank you for your attention!
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